Master of Science in Civil Engineering (MSCE)
Civil and Environmental Engineering
The primary goal of this study is to modify the original strategy developed by Cheng and Ishak (2013) into an agent-based dynamic feedback-control toll pricing strategy that accounts for the trip purpose, travel time reliability, departure time choice and level of income such that the toll revenue is maximized while maintaining a minimum desired level of service on the managed lanes. An external module was developed to execute the modified strategy. An agent-based modeling was applied to simulate drivers’ learning process based on their previous commuting experience. The study also analyzed how driver’s heterogeneity in value of time, value of reliability for each trip purpose will influence route decisions and thus affect the optimal toll rates. A numerical example was given to explain the modified strategy. The simulation results confirmed that under high traffic demand, drivers with urgent trip purpose have the highest probability of choosing managed lanes, and that the travel time on the managed lanes is more reliable than that on the general purpose lanes. A comparative evaluation is given between the modified strategy, the strategy currently deployed on Interstate 95 express lanes, and the original strategy. Compared to the current strategy, the increase in toll rate is steadier and the toll revenue is significantly higher for the modified strategy, while keeping the speed higher than 45 mph. On the other hand, compared to the original strategy, the modified one offers a more realistic approach that accounts for travel time reliability and delay in route choice and departure time choice, as well as generates higher toll revenue under heavy traffic demand.
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Li, Wan, "Accounting for Travel Time Reliability, Trip Purpose and Departure Time Choice in an Agent-Based Dynamic Feedback-Control Toll Pricing Approach" (2014). LSU Master's Theses. 2194.